scholarly journals Immune cell infiltration characteristics and related core genes in lupus nephritis: results from bioinformatic analysis

2019 ◽  
Author(s):  
Yiling Cao ◽  
Weihao Tang ◽  
Wanxin Tang
Keyword(s):  
Gene Expression ◽  
Lupus Nephritis ◽  
Molecular Mechanisms ◽  
Immune Cell ◽  
Expression Profiles ◽  
Gene Set Enrichment Analysis ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Spearman Correlation ◽  
Core Genes

Abstract Background Lupus nephritis (LN) is a common complication of systemic lupus erythematosus that presents a high risk of end-stage renal disease. In the present study, we used CIBERSORT and gene set enrichment analysis (GSEA) of gene expression profiles to identify immune cell infiltration characteristics and related core genes in LN. Results Datasets from the Gene Expression Omnibus, GSE32591 and GSE113342, were downloaded for further analysis. The GSE32591 dataset, which included 32 LN glomerular biopsy tissues and 14 glomerular tissues from living donors, was analyzed by CIBERSORT. Different immune cell types in LN were analyzed by the Limma software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis based on GSEA were performed by clusterProfiler software. Lists of core genes were derived from Spearman correlation between the most significant GO term and differentially expressed immune cell gene from CIBERSORT. GSE113342 was employed to validate the association between selected core genes and clinical manifestation. Five types of immune cells revealed important associations with LN, and monocytes emerged as having the most prominent differences. GO and KEGG analyses indicated that immune response pathways are significantly enriched in LN. The Spearman correlation indicated that 15 genes, including FCER1G, CLEC7A, MARCO, CLEC7A, PSMB9, and PSMB8 , were closely related to clinical features. Conclusions This study is the first to identify immune cell infiltration with microarray data of glomeruli in LN by using CIBERSORT analysis and provides novel evidence and clues for further research of the molecular mechanisms of LN.

scholarly journals Immune cell infiltration characteristics and related core genes in lupus nephritis: results from bioinformatic analysis

2019 ◽  
Author(s):  
Yiling Cao ◽  
Weihao Tang ◽  
Wanxin Tang
Keyword(s):  
Gene Expression ◽  
Lupus Nephritis ◽  
Molecular Mechanisms ◽  
Immune Cell ◽  
Expression Profiles ◽  
Gene Set Enrichment Analysis ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Spearman Correlation ◽  
Core Genes

Abstract Objects Lupus nephritis (LN) is a common complication of systemic lupus erythematosus that presents a high risk of end-stage renal disease. In the present study, we used CIBERSORT and gene set enrichment analysis (GSEA) of gene expression profiles to identify immune cell infiltration characteristics and related core genes in LN. Methods Datasets from the Gene Expression Omnibus, GSE32591 and GSE113342, were downloaded for further analysis. The GSE32591 dataset, which included 32 LN glomerular biopsy tissues and 14 glomerular tissues of living donors, was analyzed by CIBERSORT. Different immune cell types in LN were analyzed by the Limma software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis based on GSEA were performed by clusterProfiler software. Lists of core genes were derived from Spearman correlation between the most significant GO term and differentially expressed immune cell gene from CIBERSORT. GSE113342 was employed to validate the association between selected core genes and clinical manifestation. Result Five types of immune cells revealed important associations with LN, and monocytes emerged to be the prominent differences. GO and KEGG analyses indicated that immune response pathways are significantly enriched in LN. The Spearman correlation indicated that 15 genes, including FCER1G, CLEC7A, MARCO, CLEC7A, PSMB9, and PSMB8, were closely related to clinical features. Conclusion This study is the first to identify immune cell infiltration with microarray data of glomeruli in LN by using CIBERSORT analysis and provides novel evidence and clues for further research of the molecular mechanisms of LN.

scholarly journals Immune cell infiltration characteristics and related core genes in lupus nephritis: results from bioinformatic analysis

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Yiling Cao ◽  
Weihao Tang ◽  
Wanxin Tang
Keyword(s):  
Gene Expression ◽  
Lupus Nephritis ◽  
Molecular Mechanisms ◽  
Immune Cell ◽  
Expression Profiles ◽  
Gene Set Enrichment Analysis ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Spearman Correlation ◽  
Core Genes

Abstract Background Lupus nephritis (LN) is a common complication of systemic lupus erythematosus that presents a high risk of end-stage renal disease. In the present study, we used CIBERSORT and gene set enrichment analysis (GSEA) of gene expression profiles to identify immune cell infiltration characteristics and related core genes in LN. Results Datasets from the Gene Expression Omnibus, GSE32591 and GSE113342, were downloaded for further analysis. The GSE32591 dataset, which included 32 LN glomerular biopsy tissues and 14 glomerular tissues from living donors, was analyzed by CIBERSORT. Different immune cell types in LN were analyzed by the Limma software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis based on GSEA were performed by clusterProfiler software. Lists of core genes were derived from Spearman correlation between the most significant GO term and differentially expressed immune cell gene from CIBERSORT. GSE113342 was employed to validate the association between selected core genes and clinical manifestation. Five types of immune cells revealed important associations with LN, and monocytes emerged as having the most prominent differences. GO and KEGG analyses indicated that immune response pathways are significantly enriched in LN. The Spearman correlation indicated that 15 genes, including FCER1G, CLEC7A, MARCO, CLEC7A, PSMB9, and PSMB8, were closely related to clinical features. Conclusions This study is the first to identify immune cell infiltration with microarray data of glomeruli in LN by using CIBERSORT analysis and provides novel evidence and clues for further research of the molecular mechanisms of LN.

scholarly journals Immune cell infiltration characteristics and related core genes in lupus nephritis: results from bioinformatic analysis

2019 ◽  
Author(s):  
Yiling Cao ◽  
Weihao Tang ◽  
Wanxin Tang
Keyword(s):  
Gene Expression ◽  
Lupus Nephritis ◽  
Molecular Mechanisms ◽  
Immune Cell ◽  
Expression Profiles ◽  
Gene Set Enrichment Analysis ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Spearman Correlation ◽  
Core Genes

Abstract Background Lupus nephritis (LN) is a common complication of systemic lupus erythematosus that presents a high risk of end-stage renal disease. In the present study, we used CIBERSORT and gene set enrichment analysis (GSEA) of gene expression profiles to identify immune cell infiltration characteristics and related core genes in LN. Results Datasets from the Gene Expression Omnibus, GSE32591 and GSE113342, were downloaded for further analysis. The GSE32591 dataset, which included 32 LN glomerular biopsy tissues and 14 glomerular tissues from living donors, was analyzed by CIBERSORT. Different immune cell types in LN were analyzed by the Limma software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis based on GSEA were performed by clusterProfiler software. Lists of core genes were derived from Spearman correlation between the most significant GO term and differentially expressed immune cell gene from CIBERSORT. GSE113342 was employed to validate the association between selected core genes and clinical manifestation. Five types of immune cells revealed important associations with LN, and monocytes emerged as having the most prominent differences. GO and KEGG analyses indicated that immune response pathways are significantly enriched in LN. The Spearman correlation indicated that 15 genes, including FCER1G, CLEC7A, MARCO, CLEC7A, PSMB9, and PSMB8 , were closely related to clinical features. Conclusions This study is the first to identify immune cell infiltration with microarray data of glomeruli in LN by using CIBERSORT analysis and provides novel evidence and clues for further research of the molecular mechanisms of LN.

scholarly journals Identification of key biomarkers and immune infiltration in systemic lupus erythematosus by integrated bioinformatics analysis

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Xingwang Zhao ◽  
Longlong Zhang ◽  
Juan Wang ◽  
Min Zhang ◽  
Zhiqiang Song ◽  
...  
Keyword(s):  
Systemic Lupus Erythematosus ◽  
Lupus Erythematosus ◽  
Immune Cell ◽  
Expression Profiles ◽  
Gene Set Enrichment Analysis ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Tissue Destruction ◽  
Systemic Lupus ◽  
Ppi Networks

Abstract Background Systemic lupus erythematosus (SLE) is a multisystemic, chronic inflammatory disease characterized by destructive systemic organ involvement, which could cause the decreased functional capacity, increased morbidity and mortality. Previous studies show that SLE is characterized by autoimmune, inflammatory processes, and tissue destruction. Some seriously-ill patients could develop into lupus nephritis. However, the cause and underlying molecular events of SLE needs to be further resolved. Methods The expression profiles of GSE144390, GSE4588, GSE50772 and GSE81622 were downloaded from the Gene Expression Omnibus (GEO) database to obtain differentially expressed genes (DEGs) between SLE and healthy samples. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichments of DEGs were performed by metascape etc. online analyses. The protein–protein interaction (PPI) networks of the DEGs were constructed by GENEMANIA software. We performed Gene Set Enrichment Analysis (GSEA) to further understand the functions of the hub gene, Weighted gene co‐expression network analysis (WGCNA) would be utilized to build a gene co‐expression network, and the most significant module and hub genes was identified. CIBERSORT tools have facilitated the analysis of immune cell infiltration patterns of diseases. The receiver operating characteristic (ROC) analyses were conducted to explore the value of DEGs for SLE diagnosis. Results In total, 6 DEGs (IFI27, IFI44, IFI44L, IFI6, EPSTI1 and OAS1) were screened, Biological functions analysis identified key related pathways, gene modules and co‐expression networks in SLE. IFI27 may be closely correlated with the occurrence of SLE. We found that an increased infiltration of moncytes, while NK cells resting infiltrated less may be related to the occurrence of SLE. Conclusion IFI27 may be closely related pathogenesis of SLE, and represents a new candidate molecular marker of the occurrence and progression of SLE. Moreover immune cell infiltration plays important role in the progession of SLE.

scholarly journals Effect of Immune Cell Infiltration on Occurrence of Pulmonary Hypertension in Pulmonary Fibrosis Patients Based on Gene Expression Profiles

2021 ◽  
Vol 8 ◽  
Author(s):  
Feng Zhu ◽  
Lili Zuo ◽  
Rui Hu ◽  
Jin Wang ◽  
Zhihua Yang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Pulmonary Hypertension ◽  
Random Forest ◽  
Pulmonary Fibrosis ◽  
Immune Cells ◽  
Cross Validation ◽  
Immune Cell ◽  
Expression Profiles ◽  
Cell Infiltration ◽  
Immune Cell Infiltration

Pulmonary hypertension (PH) is a frequent complication in patients with pulmonary fibrosis (PF), whereas the mechanism was not well-understood. This study aimed to explore the influence of immune cell infiltration on PH status based on the genomic expression profiles. Microarray data of GSE24988 were downloaded from the GEO database, including 116 lung tissue samples derived from PF patients with various PH status. Proportion of infiltrated immune cells was evaluated using CIBERSORT, a gene expression-based de-convolution algorithm. A random forest classifier was constructed and out of bag (OOB) cross-validation was carried out for PH prediction. The proportions of immune infiltration cells varied differently in PH samples except T regulatory cells (p-value = 0). Compared with non-PH samples, increased number of naive B cells and plasma cells were identified in PH samples, whereas activated dendritic cells and M2 macrophages were relatively lower (p < 0.05). In the random forest model, these four types of immune cells obtained a higher variable importance score than other cells, including mean decreased accuracy and mean decreased gini evaluation. We ran the OOB cross-validation in each sample of datasets (training set and testing set) and obtained 79 and 69% accuracy, respectively. Abnormal proportions of four types of immune cells were identified in PH samples compared with non-PH samples, suggesting their involvement in PH development. In summary, the immune cell infiltration in PF patients is associated with the PH status of patients, which deserves further investigation in the future.

scholarly journals Identification of Molecular Markers Associated With the Pathophysiology and Treatment of Lupus Nephritis Based on Integrated Transcriptome Analysis

2020 ◽  
Vol 11 ◽  
Author(s):  
Menghui Yao ◽  
Congcong Gao ◽  
Chunyi Zhang ◽  
Xueqi Di ◽  
Wenfang Liang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Molecular Markers ◽  
Molecular Docking ◽  
Lupus Nephritis ◽  
Rna Sequencing ◽  
Immune Cell ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Cell Infiltration ◽  
Immune Cell Infiltration

Lupus nephritis (LN) is a well-known complication of systemic lupus erythematosus and is its leading cause of morbidity and mortality. Our study aimed to identify the molecular markers associated with the pathophysiology and treatment of LN. The renal tissue gene expression profiles of LN patients in the GSE32591 dataset were downloaded as a discovery cohort from the Gene Expression Omnibus. Differentially expressed genes (DEGs) were identified; weighted gene co-expression network analysis (WGCNA) was used to identify the co-expression modules of DEGs; and gene function enrichment analysis, molecular crosstalk analysis, and immune cell infiltration analysis were performed to explore the pathophysiological changes in glomeruli and tubulointerstitia of LN patients. The crosstalk genes were validated in another RNA-sequencing cohort. DEGs common in RNA-sequencing dataset and GSE32591 were uploaded to the Connectivity Map (CMap) database to find prospective LN-related drugs. Molecular docking was used to verify the targeting association between candidate small molecular compounds and the potential target. In all, 420 DEGs were identified; five modules and two modules associated with LN were extracted in glomeruli and tubulointerstitia, respectively. Functional enrichment analysis showed that type I interferon (IFN) response was highly active, and some biological processes such as metabolism, detoxification, and ion transport were impaired in LN. Gene transcription in glomeruli and tubulointerstitia might affect each other, and some crosstalk genes, such as IRF7, HLA-DRA, ISG15, PSMB8, and IFITM3, play important roles in this process. Immune cell infiltration analysis revealed that monocytes and macrophages were increased in glomeruli and tubulointerstitia, respectively. CMap analysis identified proscillaridin as a possible drug to treat LN. Molecular docking showed proscillaridin forms four hydrogen bonds with the SH2 domain of signal transducer and activator of transcription 1 (STAT1). The findings of our study may shed light on the pathophysiology of LN and provide potential therapeutic targets for LN.

scholarly journals Germline genetic polymorphisms influence tumor gene expression and immune cell infiltration

2018 ◽  
Vol 115 (50) ◽  
pp. E11701-E11710 ◽  
Author(s):  
Yoong Wearn Lim ◽  
Haiyin Chen-Harris ◽  
Oleg Mayba ◽  
Steve Lianoglou ◽  
Arthur Wuster ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cancer Immunotherapy ◽  
Genetic Variants ◽  
Immune Cell ◽  
Response To Therapy ◽  
Cell Infiltration ◽  
Cancer Type ◽  
Immune Cell Infiltration ◽  
Durable Response ◽  
The Impact

Cancer immunotherapy has emerged as an effective therapy in a variety of cancers. However, a key challenge in the field is that only a subset of patients who receive immunotherapy exhibit durable response. It has been hypothesized that host genetics influences the inherent immune profiles of patients and may underlie their differential response to immunotherapy. Herein, we systematically determined the association of common germline genetic variants with gene expression and immune cell infiltration of the tumor. We identified 64,094 expression quantitative trait loci (eQTLs) that associated with 18,210 genes (eGenes) across 24 human cancers. Overall, eGenes were enriched for their being involved in immune processes, suggesting that expression of immune genes can be shaped by hereditary genetic variants. We identified the endoplasmic reticulum aminopeptidase 2 (ERAP2) gene as a pan-cancer type eGene whose expression levels stratified overall survival in a subset of patients with bladder cancer receiving anti–PD-L1 (atezolizumab) therapy. Finally, we identified 103 gene signature QTLs (gsQTLs) that were associated with predicted immune cell abundance within the tumor microenvironment. Our findings highlight the impact of germline SNPs on cancer-immune phenotypes and response to therapy; and these analyses provide a resource for integration of germline genetics as a component of personalized cancer immunotherapy.

scholarly journals A novel pyroptosis-associated gene signature for immune status and prognosis of cutaneous melanoma

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e12304
Author(s):  
Zhengyuan Wu ◽  
Leilei Chen ◽  
Chaojie Jin ◽  
Jing Xu ◽  
Xingqun Zhang ◽  
...  
Keyword(s):  
Cutaneous Melanoma ◽  
Immune Status ◽  
Immune Cell ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Tumor Cell Death ◽  
Prognostic Gene ◽  
Prognostic Gene Signature

Background Cutaneous melanoma (CM) is a life-threatening destructive malignancy. Pyroptosis significantly correlates with programmed tumor cell death and its microenvironment through active host-tumor crosstalk. However, the prognostic value of pyroptosis-associated gene signatures in CM remains unclear. Methods Gene profiles and clinical data of patients with CM were downloaded from The Cancer Genome Atlas (TCGA) to identify differentially expressed genes associated with pyroptosis and overall survival (OS). We constructed a prognostic gene signature using LASSO analysis, then applied immune cell infiltration scores and Kaplan-Meier, Cox, and pathway enrichment analyses to determine the roles of the gene signature in CM. A validation cohort was collected from the Gene Expression Omnibus (GEO) database. Results Four pyroptosis-associated genes were identified and incorporated into a prognostic gene signature. Integrated bioinformatics findings showed that the signature correlated with patient survival and was associated with tumor growth and metastasis. The results of Gene Set Enrichment Analysis of a risk signature indicated that several enriched pathways are associated with cancer and immunity. The risk signature for immune status significantly correlated with tumor stem cells, the immune microenvironment, immune cell infiltration and immune subtypes. The expression of four pyroptosis genes significantly correlated with the OS of patients with CM and was related to the sensitivity of cancer cells to several antitumor drugs. A signature comprising four genes associated with pyroptosis offers a novel approach to the prognosis and survival of patients with CM and will facilitate the development of individualized therapy.

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